High energy, real time capable, direct radiation conversion X-ray imaging system for Cd-Te and Cd-Zn-Te based cameras

ABSTRACT

A calibrated real-time, high energy X-ray imaging system is disclosed which incorporates a direct radiation conversion, X-ray imaging camera and a high speed image processing module. The high energy imaging camera utilizes a Cd—Te or a Cd—Zn—Te direct conversion detector substrate. The image processor includes a software driven calibration module that uses an algorithm to analyze time dependent raw digital pixel data to provide a time related series of correction factors for each pixel in an image frame. Additionally, the image processor includes a high speed image frame processing module capable of generating image frames at frame readout rates of greater than ten frames per second to over 100 frames per second. The image processor can provide normalized image frames in real-time or can accumulate static frame data for substantially very long periods of time without the typical concomitant degradation of the signal-to-noise ratio.

FIELD OF THE INVENTION

The present invention is in the field of semiconductor imaging systemsfor imaging x-ray and gamma ray radiant energy. More specifically, theinvention relates to a high energy charge-integrating imaging devicesutilizing Cd—Te or Cd—Zn—Te based detector substrates in combinationwith CMOS readout substrates. Additionally, the invention relates to aprocess for calibrating such high energy radiation imaging systems.

BACKGROUND OF THE INVENTION

Over the past ten years digital radiation imaging has gradually beenreplacing conventional radiation imaging for certain applications. Inconventional radiation imaging applications, the detecting or recordingmeans is a photosensitive film or an analog device such as an ImageIntensifier. Digital radiation imaging is performed by convertingradiation impinging on the imaging device (or camera) to an electronicsignal and subsequently digitizing the electronic signal to produce adigital image.

Digital imaging systems for producing x-ray radiation images currentlyexist. In some such devices, the impinging or incident radiation isconverted locally, within the semiconductor material of the detector,into electrical charge which is then collected at collectioncontacts/pixels, and then communicated as electronic signals to signalprocessing circuits. The signal circuits perform various functions, suchas analog charge storing, amplification, discrimination and digitizationof the electronic signal for use to produce an digital imagerepresentation of the impinging radiation's field strength at theimaging device or camera. These types of imaging systems are referred toas “direct radiation detection” devices.

In other devices, the impinging radiation is first converted into lightin the optical or near optical part of the visible light spectrum. Thelight is subsequently converted to an electronic signal using photodetector diodes or the like, and the resultant electronic signal is thendigitized and used to produce a digital image representation of theimpinging radiation's field strength at the imaging device or camera.This type of imaging system is referred to as an “indirect radiationdetection” device.

Currently, operation of a flat panel imaging device/camera (of eitherthe direct type or indirect type of detector) typically involvescollecting and integrating a pixel's charge over a period of time andoutputting the resultant analog signal which is then digitized. Presentcharge integration times are typically from 100 msec to several seconds.Devices presently available in the field are suitable for singleexposure digital x/gamma-ray images, or for slow multi-frame operationat rates of up to 10 fps (frames per second). The digitization accuracytypically is only about 10 bits, but can be 14 to 16 bits if the chargeintegration time is sufficiently long. The high end of digitizationaccuracy currently is accomplished in imaging systems wherein thetypical charge integration times range from several hundred millisecondsup to a few seconds. Therefore, in these current imaging systems,increasing accuracy requires increasing the pixel charge integrationtime. Unfortunately, errors inherent in current imaging systems limitthe length of a charge integration cycle to just a few seconds at most,before the signal-to-noise ratio first “saturates” and then becomes sobad as to preclude any increase in accuracy with increasing chargeintegration time.

In any event, it is the cumulative integrated analog signal that isreadout from the camera and digitized. Then calibration is applied tocorrect the non-uniformities inherent in flat panel imaging device, andmore rarely to correct the non-linear behavior of the imaging systemitself.

Designing and manufacturing a sensitive, high energy radiation-imagingdevice is a very complex task. All the device's structural modules andperformance features must be carefully designed, validated, assembledand tested before a fully functioning camera can be constructed.Although great progress has been made in the research and development ofsemiconductor radiation imaging devices, a large number of oldperformance issues remain and certain new performance issues havedeveloped. Some of the new performance issues result from solving othereven more severe performance problems, while some are intrinsic to theoperating principle of such devices.

High energy “direct radiation detector” type x-ray imaging systemstypically utilize semiconductor detector substrate composed of Cd—Te orCd—Zn—Te compositions. The Cd—Te or the Cd——Zn—Te detector substrate istypically bump-bonded to a CMOS readout (signal processing) substrate.It can also be electronically connected to the CMOS readout with the useof conductive adhesives (see US Patent Publication No. 2003/0215056 toVuorela). Each pixel on the CMOS readout substrate integrates the chargegenerated from the absorption the impinging x/gamma rays in thethickness of material of the detector substrate. The known performanceimpacting issues with Cd—Te or Cd—Zn—Te/CMOS based charge-integrationdevices can be divided into two major areas: electrical performanceproblems and materials/manufacturing defects. Electrical performanceproblems can be further subdivided into six different though partiallyoverlapping problems: leakage current, polarization or charge trapping,temporal variation, temperature dependency, X-ray field non-uniformity,and spectrum dependency. Materials/manufacturing defects problems canalso be further subdivided into: Cd—Te or Cd——Zn—Te detector materialissues, CMOS-ASIC production issues, and overall device manufacturingissues.

The main reasons for use of crystalline compound semiconductors such asCdTe and CdZnTe in the detector substrate of a charge-integratingimaging device is their superb sensitivity, excellent pixel resolution,and quick response (very little afterglow) to incoming radiation. On theother hand, current methods of producing Cd—Te and Cd—Zn—Te flat panelsubstrates limits their uniformity and impacts the crystal defect rateof these materials, which as can cause some of the problems mentionedabove. In addition, due to the use of an electric field of the order of100V/mm or higher, a considerable leakage current (or dark current)results, causing image degradation.

Prior descriptions of Cd—Te or Cd——Zn—Te based x-ray/gamma ray imagingdevices exist. For example, U.S. Pat. No. 5,379,336 to Kramer et al. andU.S. Pat. No. 5,812,191 to Orava et al. describe generally the use ofCd—Te or Cd—Zn—Te semiconductor detector substrates bump-bonded to ASICssubstrates of a charge-integration type digital imaging camera. However,these documents make no mention of and do not address the issues arisingwhen a device of this type operates at high frame rates exceeding 10fps, or how to calibrate, or even the need to calibrate in the case ofsuch an application. Another example is European Patent EP0904655, whichdescribes an algorithm for correcting pixel values of a Cd—Te orCd—Zn—Te imaging device. However the issue of operating the device athigh rates and how to compose an image from many uncorrected individualframes is not addressed. EP0904655 simply provides a correctionalgorithm for correcting pixel values from a single exposure andconsequently displaying such pixel values.

Although these prior devices and methods may be useful each for itsintended purpose, it would be beneficial in the field to have a highenergy x-ray, real time imaging system that provides both increasedimage frame readout rates of substantially greater than 1 Ofps andgreater than 16 bit accuracy. For example, it would be useful in thefields of panoramic dental imaging, cephalometry, and computerizedtomography to have high energy X-ray imaging systems with both increaseframe readout rates and high accuracy. Even static imaging applications,where the exposure time is a multiple of the single frame duration, itwould be useful to have such an imaging system.

SUMMARY OF THE INVENTION

The present invention is a high energy, direct radiation conversion,real time X-ray imaging system. More specifically, the present real timeX-ray imaging system is in tended for use with Cd—Te and Cd—Zn—Te basedcameras. The present invention is particularly useful in X-ray imagingsystems requiring high image frame acquisitions rates in the presence ofnon linear pixel performance. The present invention is “high energy” inthat it is intended for use with X-ray and gamma ray radiation imagingsystems having a field strength of 1 Kev and greater. The high energycapability of the present X-ray imaging system is derived from itsutilization of detector substrate compositions comprising Cadmium andTelluride (e.g., Cd—Te and Cd——Zn—Te based radiation detectorsubstrates) in the imaging camera. Cd—Te and Cd——Zn—Te based detectorsubstrates define the present invention as being a direct radiationconversion type detector, because the impinging radiation is directlyconverted to electrical charge in the detector material itself.

The detector substrate is a monolith and has a readout face or surfacewhich is highly pixelized, i.e., it has a high density pattern of pixelcharge collectors/electrodes on it. The pattern is high density in thatthe pitch (distance from center-to-center) of the pixel chargecollectors is 0.5 mm or less. Each pixel's collector/electrode is inelectrical communication (e.g., via electrical contacts such asbump-bonds or conductive adhesives) to the input of a pixel readout ASICon the readout/signal processing substrate. The detector substrateprovides for directly converting incident x-rays or gamma radiation toan electrical charge and for communicating the electrical charge signalsvia the pixel electrical contact to the readout ASIC. The readout/signalprocessing ASIC provides for processing the electrical signal from itsassociated pixel as necessary (e.g., digitizing, counting and/or storingthe signal) before sending it on for further conditioning and display.The capability of the present invention to be read out at high framerates enables the real time imaging feature. Real time imaging refers tothe capability of the system to generate image frames for display insufficiently rapid succession to provide a moving picture record inwhich movement appears to occur substantially real time to the humaneye.

Descriptions of flat panel x-ray imaging cameras substantially analogousto the intended Cd—Te or a Cd——Zn—Te based charge-integrating detectorbonded to an ASIC readout/signal processing substrate are known in theart. Examples are disclosed in US Patent Application Publication serialnumber 2003-0155516 to Spartiotis et al. relating to a Radiation ImagingDevice and System, and US Patent Application Publication serial number2003-0173523 to Vuorela relating to a Low Temperature, Bump-BondedRadiation Imaging Device, which documents are incorporated herein byreference as if they had been set forth in their entirety.

In a preferred embodiment of the present imaging system, the imagingdevice or camera is “readout” at a high frame rate. A high frame rate asused herein means that the accumulation and distribution of electricalcharge developed in the detector semiconductor substrate is utilized(“readout”) to produce a digital image frame at a rate greater thanabout 10 individual image frames per second up to 50 and greaterindividual image frames per second. An individual image frame is adigital representation of the active area (pixel pattern) of thecamera's detector substrate. An image frame is generated each time theASIC substrate is readout. The digital representation can be describedas a matrix of digitized individual pixel signal values. That is, eachpixel value of each pixel in the image frame is a digitizedrepresentation of the intensity of the electronic signal level readoutfor the corresponding specific pixel on the detector substrate.

Additionally, each pixel value in the image frame includes an individualcalibration correction specific to that pixel value, and therefore infact is a corrected digital pixel value. The specific calibrationcorrection for each image pixel is derived from the present pixel valuecorrection calibration process. The individual corrected digital pixelvalues of the same specific image pixel from different image frames isprocessed according to an algorithm of the calibration process over atleast some of the collected image frames to provide the pixel value tobe displayed in the final image. Therefore, it is a further object ofthe present invention to provide a calibration (or correction) method toenable the current invention to be implemented. The calibration methodis applicable on each pixel of the imaging system and takes into accountthe offset and gain corrections as well as temporal (time) correctionsas this is applied on a frame by frame basis. There maybe no need tohave different correction for each pixel and each frame but inaccordance with the current invention at least some of the frames havedifferent temporal correction for corresponding pixels.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram generally illustrating the interconnectrelationship of components of the present high energy, direct radiationconversion, real time X-ray imaging system

FIG. 2 is a schematic representation of an imaging device useful in thecamera module of the present invention.

FIG. 3 is a graphic representation of the output over time of a singlepixel circuit of a Cd—Te based direct conversion camera using detectorbias voltage switching. The figure illustrates that the output signalfrom a typical pixel circuit drifts over time as circuit recovers from abias voltage switching event (pulse).

FIG. 4 is a graph illustrating the temporal variation in the rawintensity value of the same single image pixel of FIG. 3 overlaid with aseries of image frame capture points generated over time after a biasvoltage switching event.

FIG. 5 is a graph illustrating normalization of the intensity value ofan image pixel by the application of a specific time dependentcorrection coefficient to the raw intensity value of the particularimage pixel's output in each image frame.

FIG. 6 is a graph illustrating an asymmetric data sampling feature ofthe calibration procedure of the present imaging system for amelioratingthe problem of excessive data collection and processing load.

FIG. 7 is a block flow chart illustrating a general overview of thepresent calibration procedure.

FIG. 8 is a block flow diagram illustrating a data collection strategyfrom a single pixel circuit at a specific reference X-ray fieldintensity.

FIG. 9 is a block flow diagram illustrating a strategy for calculatingcorrection coefficients for each image pixel in a pixel frame.

FIG. 10 is a block flow diagram illustrating a strategy for detectingand compensating for bad or uncorrectable pixels.

FIG. 11 is a block flow diagram illustrating the application of thepresent calibration process to provide a normalize image frame.

FIG. 12A is a graph illustrating the typical prior uniform samplingmethod wherein an integration by uniform parts type calculation is usedto determine correction coefficient for normalizing pixel intensityvalues at specific times or intensities to fit a curve.

FIG. 12B is a graph illustrating an asymmetric sampling method whereinan integration by increasing parts type calculation is used to determinecorrection coefficients for normalizing pixel intensity values atspecific times.

FIG. 12C is a graph illustrating an alternative sampling method whereinan asymmetric linear polynomic calculation is used to determinecorrection coefficients for normalizing pixel intensity values atspecific times.

DETAILED DESCRIPTION OF THE INVENTION

Referring now to the drawings, the details of preferred embodiments ofthe present invention are graphically and schematically illustrated.Like elements in the drawings are represented by like numbers, and anysimilar elements are represented by like numbers with a different lowercase letter suffix.

As illustrated in FIG. 1, the present invention is a high energy,real-time capable, direct radiation conversion X-ray imaging system 10.More specifically, the present invention relates to such X-ray imagingsystems 10 utilizing a Cd—Te or Cd——Zn—Te based camera. The presentreal-time capable X-ray imaging system 10, like imaging systemsgenerally, comprises a camera module, an image processor 14, and adisplay means 16. In the present real-time X-ray imaging system 10, thecamera module 12 includes an X-ray imaging device 28 having a Cd—Te orCd——Zn—Te based radiation detector substrate 30 in electricalcommunication with an Application Specific Integrated Circuit (ASIC)readout substrate 32. Each active pixel 36 on the detector 30 iselectrically connected to a corresponding pixel circuit 31 on the ASICreadout substrate 32.

FIG. 2. is a schematic representation of an imaging device 28 useful inthe camera module 12 of the present imaging system 10. In these imagingdevices 28 as generally exemplified in FIG. 2, the detectorsemiconductor substrate 30 has electrical connections 35 to an readoutASIC substrate 32 (e.g., bump-bonds in the preferred embodimentillustrated). The detector material 34, a Cadmium-Telluride basedcomposition in the present invention, of the semiconductor substrate 30absorbs incoming radiation, and in response to the absorption theradiation energy is directly converted to electrical charges within thethickness of the detector material 34. The electrical charges arecollected at the detector pixel's collection electrode (pixel contact)38 of each active or functioning pixel 36, and electrically communicatedthrough the electrical connections 35 to the pixel circuit contacts 33on the pixel circuit 31 of the readout ASIC substrate 32. The electriccharge signals are stored and/or processed at a detector pixel'scorresponding pixel circuit 31 on the readout ASIC 32. Thereafter, theASIC pixel circuits 31 are usually multiplexed and an analog output issequenced and digitized either on chip or off-chip.

The camera module 12 and the high speed frame processor module 18 are incommunication via a cable link 60. The camera module 12 providesprocessed and organized pixel data, representing the individual rawpixel circuit output of each pixel cell 29, to the frame processormodule 18. The high speed frame processor module 18 includes a framegrabber circuit typical of the field, which captures the pixel circuitdata from the camera module 12 further processes the pixel circuit datato provide a raw time-stamped image frame representing the raw pixelcircuit output of each pixel cell 29. The frame processor 18 thencommunicates the raw time-stamped image frame data via a frame data link66 to the calibration module 20 if the system is in the calibrationmode, or otherwise to the normalization module 24.

The calibration module 20 controls the calibration process. Thecalibration process analyzes the raw time-stamped image frame data andother calibration parameters, such as reference field radiationintensity, and generates the data necessary to load the look-up table ofthe calibration data structure module 22. The calibration module 20writes to the data structure via a database link 68. Without propercalibration data loaded into the look-up table, any image output fromthe normalization module 24 to the display module will be inaccurate.Therefore, the calibration process must be run prior to normal imagingoperation of the present system.

When not in calibration mode, the frame processor 18 communicates thetime-stamped image frame data to the normalization module 24. Thenormalization module 24 operates on each image pixel of the rawtime-stamped image frame with the image pixel's corresponding correctionrequirement derived from the look-up table via a second database link70. The normalization module 24 then provides a normalized image frameto the display module 16 via a display data link 74. Every image pixelof the normalized image frame represents its corresponding raw imagepixel intensity value corrected by its corresponding correctioncoefficient from the look-up table.

To obtain a high quality image, several obstacles need to be overcome inrelation to Cadmium-Telluride based detector substrates 30. For example,there is a continuous leakage current (aka: dark current) that must becompensated for. Certain Cd—Te or Cd——Zn—Te detector materials 34 aremanufactured having a blocking contact (not shown) to control the levelof leakage current. Other manufactures have various amounts of Zn orother dopants in the detector material 34 to suppress leakage current.In any event, the leakage current creates noise and also fills up thecharge collection gates 33 on each pixel circuit 31. Additionally theuse of blocking contacts introduces the problem of polarization orcharge trapping which becomes evident after few seconds of operation,for example, after 5 sec, 10 sec or 60 sec etc., depending on thedevice.

The advantage of using Cadmium-Telluride based compositions (i.e., Cd—Teand Cd——Zn—Te) as the radiation absorption medium 34 in the presentdetector substrate 30 is their very high radiation absorptionefficiency, minimal afterglow and their potential for high imageresolution. Therefore, it is valuable to have imaging systems thatmitigate or eliminate the above issues. Even in the absence of ablocking contact the issue of the leakage current and crystal defects donot allow long exposures in excess of 100 msec without increasing thesize of the charge storage capacitor on each pixel circuit 31 of theASIC readout substrate 32. However, this would be to the detriment ofsensitivity because the larger the charge storage capacitance is, thelower the sensitivity becomes. For example, the present invention hasbeen successfully practiced using a capacitance of the order 50 fF ascharge storage capacitance on each ASIC pixel circuit receiving charge.With this size of capacitance, the practical maximum exposure time giventhe Cd—Te or Cd——Zn—Te leakage current and other defects would be 100msec or less.

A very useful mechanism for preventing excessive polarization (chargetrapping) from forming in a direct conversion (charge coupled) radiationdetector device is to briefly cycle the high voltage bias off and on, atechnique called detector bias voltage switching. To utilize thistechnique, the detector substrate bias voltage is switched off for abrief period (less than 100 milliseconds) at the end of a datacollection cycle. The duration of a data collection cycle is selectable,e.g., from every three to twenty or more seconds. Bias voltage switchingprevents polarization or charge trapping from developing in the detectorsubstrate 30. However, the bias voltage switching technique is new inthe field of X-ray imaging systems, and does have certain aspects thatcan impact image quality if the are not addressed. One such aspect is“dead-time,” and the other is “pixel response drift.” “Dead-time” is theperiod in a data collection cycle when the detector bias voltage is offand no detector charges can be collected. “Pixel response drift” is athe result of switching the detector bias voltage back on, and is theinitial period that the data collection cycle that the that the pixel'sresponse to a static radiation field has not yet stabilized. Both ofthese limitations are illustrated in FIG. 3.

For the purpose of the embodiment illustrated in FIG. 3, the datacollection cycle time Ct was the time between the initiation of detectorbias voltage off/on pulses 50. The dead-time Dt consists of the actualhigh voltage down-time Vo plus some stabilization time after the highvoltage has been switched back on. The effect of dead-time Dt cannot beless than Vo, and hence cannot be completely eliminated in a switcheddetector bias voltage imaging system. However, it can be minimized inpart by reducing the off-time of the bias voltage to as short a periodas is appropriate to allow any polarization (trapped charge) to bleedoff and/or to keep the dead-time to a negligibly small portion of thedata collection cycle.

The other potentially limiting aspect of a bias voltage switcheddetector is pixel response drift Rd, which relates to the non-linearaspect of a pixel circuit's output signal over time 40 in response to astatic radiation field exposure level. See FIG. 3. This non-linearity ismost pronounced immediately following the voltage-on step of the voltageoff-on pulse 50. Uncorrected, this non-linearity causes pumping of theimage's overall brightness level in a real time image display. The pixelcell non-linear response in a switched bias voltage imaging device is anexcellent case for applying the post-image frame generation calibrationmethod of the present imaging system to eliminate this intensitydistortion of a real time X-ray image display.

The present calibration method 10 is especially useful for practice indigital imaging systems utilizing detector bias voltage switching. Thecamera module 12 of a digital imaging system utilizing detector biasvoltage switching typically comprises a detector/CMOS assembly 28 havingthousands of pixel cells 29, each comprising a detector pixel 36 and anassociated pixel circuit 31. Each pixel circuit 31 includes associatedcircuitry and a pixel circuit signal output (not shown) producing adigitized pixel signal for that pixel circuit 31. A pixel circuit outputsignal indicates the intensity of the X-ray/Gamma ray radiation energyimpinging on the associated detector pixel 36. See FIG. 2.

The collected digitized pixel signal outputs are communicated via acamera link 60 to a high speed frame processor module 18 of the imageprocessor 14. The frame processor module 18 includes a frame grabbercircuit which receives the individual pixel circuit output signals fromeach pixel circuit 31. The frame processor module 18 organizes theindividual digitized pixel signals into an image frame, with each imagepixel of the image frame representing the pixel signal of acorresponding to the pixel circuit in the imaging device 28 of thecamera module 12. The intensity of an image pixel in the image frame isrepresentative of the strength of the pixel signal received from thecorresponding pixel circuit 31. However, because of the inherentdifferences in the mechanical and electrical properties of theindividual constituents of each pixel cell 29, the intensity response ofthe various pixels comprising an image frame are not uniform, even inresponse to a uniform x-ray field. Therefore, calibration of the imagingsystem is necessary before the information represented by the imageframe is useful to a user.

The Calibration Procedure

FIG. 7 is an overview of the steps of the calibration process of thepresent imaging system. FIGS. 8 to 10 detail the calibration procedure.FIG. 11 details the normalization procedure, wherein the raw image pixeldata from the frame processor module is normalized. The calibrationprocess uses a software driven calibration module 20 to create andmaintain a “look-up table” resident in a data structure module 22. Thelook-up table is a set of time dependent, image pixel specificcorrection coefficients 54 for each pixel of an image frame. The pixelspecific correction values 54 are referenced to a target uniformintensity value 52 (see FIG. 5), and are used to correct the raw valueof the specific image pixel to a normalized value. Therefore, each imagepixel represented in an image frame has a data set of time dependentcorrection coefficients in the look-up table of the data structuremodule 22 generated for each of a number of reference x-ray fieldintensities.

The time dependency of a set of correction coefficients/values derivesfrom the application of a time-stamp to each image frame processed bythe high speed frame module. The time-stamp indicates the time elapsedsince the start of the data collection cycle Ct that the image frame wasgenerated. In the preferred embodiment illustrated in FIG. 4, the timestamped image frames 44 were captured (grabbed) from the camera module12 at uniform frame intervals 46 in the data collection cycle Ct.Therefore, the time-stamped image frames 44 always had the same timedifference relative to each other. The first frame grabbed afterdetector bias voltage was switched on was assigned time-stamp=0, secondhad time-stamp=1, and so on up to time-stamp=N. In practice, a separatecalibration data set was calculated for each image pixel and included acorrection value for that specific image pixel at each time-stamp in thedata collection cycle Ct. Alternatively, the calibration data can bethought of or organized as consisting of N different calibration datasets, one for each image frame of the data collection cycle Ct, eachframe data set comprising a separate correction value/coefficient foreach image pixel in the frame. For best image quality, N should beselected as the highest number of different time stamps possibleN_(max), or in other words, the highest frame rate possible. However,this would be an extremely data intensive condition and due to currentlimitations in the technology, e.g., limited computer memory processingtimes, an N<N_(max) has to be selected.

Collecting the data. First step in the calibration method is to collectthe relevant data, specifically, the response of the camera's imagingdevice 28 to different reference radiation field intensities. Theresponse of each pixel cell 29 of the device 28 is collected for all thetime-stamps in the data collection cycle Ct. In the preferred embodimentillustrated, this step was repeated at least 20 times, to reduce theeffect of incoming quantum noise. Collecting the relevant data this waycorrects for any non-uniformities in the detector or ASIC components,but also intrinsically provides “flat-field” correction. In thisembodiment, the calibration method tied the imaging device 28 of thecamera module 12 to a specific geometric relationship with the radiationsource. Which is to say, the calibration had to be redone whenever theradiation source or the geometry between the imaging device 28 and theradiation source changed. Also, calibration was repeated for eachradiation spectrum used.

Calculation of Pixel Specific Correction Coefficients/Values. Theresponse of a single pixel cell 29 as a function of time and withexposure to different reference radiation field intensities has acharacteristic shape. The basic idea behind the present calibrationmethod is uniformity. Each and every pixel cell 29 should give the samepixel output signal if exposed to the same intensity of radiation. Thismeans that the calibration functiony _(out) =f _(pix)(x _(in))  (1)is a mapping from pixel output values x_(in) to global output valuesy_(out). The task is to find suitable functions f_(pix)( ) for eachpixel that gives the same output as all the other pixels.

The choice to use polynomials was made because they are extremely fastto calculate, which was absolutely necessary for real-time operation.The polynomials are not the best basis for regression problems likethis, because of their unexpected interpolation and extrapolationbehavior. The function f_(pix)( ) can now be explicitly written as:$\begin{matrix}{y_{out} = {\sum\limits_{i = 0}^{M}{a_{i_{,{pix}}}x_{in}^{i}}}} & (2)\end{matrix}$where a_(i,pix) are the coefficients for pixel pix and M is the order ofthe polynomial. The commonly used linear calibration (gain and offsetcorrection) is a special case when M=1. Use of 3^(rd) order polynomialwas the basis of the current embodiment, but linear correction was notsufficient to remove all the non-uniformities.

Estimating calibration parameters. A common way of estimating modelparameters in a regression problem like this is to use a MaximumLikelihood (ML) estimation. This means that we maximize the likelihoodof all the data points for a one pixel at a time given the function andnoise model. Assuming normally distributed zero-mean noise, theprobability of one data sample x_(i) is: $\begin{matrix}{{p\left( {\left. x_{i} \middle| \sigma \right.,f} \right)} = {\frac{1}{\sqrt{2\quad\pi}\sigma^{2}}\quad{{Exp}\left( {- \frac{\left( {x - {f(x)}} \right)}{2\quad\sigma^{2}}} \right)}}} & (3)\end{matrix}$and the total likelihood for all the samples assuming they arestatistically independent is: $\begin{matrix}\begin{matrix}{{LL} = {\prod\limits_{i = 1}^{N_{data}}{p\left( {\left. x_{i} \middle| \sigma \right.,f} \right)}}} \\{= {\left( \frac{1}{\sqrt{2\quad\pi}\sigma^{2}} \right)^{N_{data}}\quad{{Exp}\left( {- {\sum\limits_{i = 1}^{N_{data}}\frac{\left( {x - {f(x)}} \right)}{2\quad\sigma^{2}}}} \right)}}}\end{matrix} & (4)\end{matrix}$

A problem with Maximum Likelihood estimation is that it is verydifficult to apply any prior knowledge accurately. To overcome this, aMaximum A Posteriori (MAP) estimation is used. In a MAP estimation, theposteriori distribution of all the samples is maximized by:$\begin{matrix}{{p\left( {\overset{¨}{E},\left. f \middle| x \right.} \right)} = \frac{{p\left( {\left. x \middle| \overset{¨}{E} \right.,f} \right)}\quad{p(f)}}{p(x)}} & (5)\end{matrix}$where L is the estimated covariance matrix of samples assumingindependence, A=diag[σ₁ . . . σ_(Ndata)], x=[x₁ . . . x_(Ndata)] is thevector of data samples and f=[f(x₁) f(x_(Ndata))] is the vector ofcalibrated values for this pixel. p(x) is the uninteresting scalingfactor, evidence. If we assume normal distribution for noise and forfunction parameter prior $\begin{matrix}{{p\left( {\left. x \middle| \overset{¨}{E} \right.,f} \right)} = {\left( {2\quad\pi} \right)^{- \frac{N_{data}}{2}}\quad{\overset{¨}{E}}^{- \frac{1}{2}}\quad{\exp\left( {{- \frac{1}{2}}\quad x^{T}\quad{\overset{¨}{E}}^{- 1}x} \right)}}} & (6) \\{{p(f)} = {\left( {2\quad\pi} \right)^{- \frac{M + 1}{2}}\quad\sigma_{prior}^{2}\quad{\exp\left( {{- \frac{1}{2\quad\sigma_{prior}^{2}}}\quad{\sum\limits_{i = 0}^{M}a_{i}^{2}}} \right)}}} & (7)\end{matrix}$then the final posteriori will have form of: $\begin{matrix}{{p\left( {\overset{¨}{E},\left. f \middle| x \right.} \right)} = \frac{\begin{matrix}{\left( {2\quad\pi} \right)^{- \frac{N_{data}}{2}}\quad{\overset{¨}{E}}^{- \frac{1}{2}}\quad{{\exp\left( {{- \frac{1}{2}}\quad x^{T}\quad{\overset{¨}{E}}^{- 1}x} \right)} \cdot}} \\{\left( {2\quad\pi} \right)^{- \frac{M + 1}{2}}\quad\sigma_{prior}^{2}\quad{\exp\left( {{- \frac{1}{2\quad\sigma_{prior}^{2}}}\quad{\sum\limits_{i = 0}^{M}a_{i}^{2}}} \right)}}\end{matrix}}{p(x)}} & (8)\end{matrix}$

If we take the natural logarithm of the formula above and group all theconstant coefficients to new ones, we will get a cost function of:$\begin{matrix}{{Cost} = {{\sum\limits_{i = 1}^{N_{data}}{\frac{1}{\sigma_{i}^{2}}\left( {x_{i} - {f\left( x_{i} \right)}} \right)^{2}}} + {\sigma_{prior}^{2}\quad{\sum\limits_{i = 0}^{M}a_{i}^{2}}}}} & (9)\end{matrix}$σ_(prior) ² which can be interpreted as a weighted and constrainedlinear least squares cost function with penalty parameter. The finalparameter values can be solved by differentiating the equation abovewith respect to all the function parameters a_(i) and then setting thederivative equal to zero. The motivation for using weighted leastsquares is that when using different X-ray intensities, the quantumnoise for the highest intensity is much higher than, for example, thedark current. This allows more weight to be given to smaller values,which are probably more accurate.

Implementation and Performance Considerations. To optimize imagequality, 32-bit floating-point arithmetic was used in all thecalculations. Current x86 processors offer good SIMD (singleinstruction, multiple data) command that allowed very efficient parallelprocessing.

Selecting Appropriate Time-Stamped Calibration Image Frames for Use inthe Correction Protocol. For practical reasons, every time-stamp in thedata collection cycle Cl cannot be used because the amount of datagenerated would be huge, and processing time and memory allocationsprohibitive in certain circumstances. This is because current largecameras offers images up to 508×512 pixels. There are 4 parameters perpixel (3^(rd) order polynomial) and each parameter is 4 bytes. Thismeans there are 3.97 MB of data collected per frame. In the currentembodiment, the camera provided 50 frames per second, which meant a datacollection rate of 198 MB/second. In addition to this, the images wereread over the PCI bus in 16-bit format (24.8 MB/second) and stored inthe memory (another 24.8 MB/second). The total data rate for 50 fpsoperation was 248 MB/second. In frame averaging mode, the previous imagevalues were also read from the memory, which gave another 24.8MB/second, and a total of 273 MB/second memory bandwidth. If the imagesare displayed on a screen, the 16-bit pixel values is read from thememory, a 32-bit color value is read from the lookup-table per pixel andthe final 32-bit values is stored in the display memory givingadditional 124 MB/second for a grand total of 397 MB/second. And thefield is moving to even larger cameras.

One pixel requires at least two 32-bit floating point numbers/frame. Fora data collection cycle time of 30 second, at a frame rate of 300 fpsand a 96000 pixel image frame would mean 6.4 GB of data generated over asingle data collection cycle. FIGS. 12A to 12C are a furtherillustration of this. FIG. 12A shows the prior art method of errorsampling. However, at 300 fps with a 30 sec data collection cycle and a100,000 pixel camera, and 4 parameters at 4 bytes/parameter, 13 GB ofdata must be collected and processed. This is impractical. FIG. 12Bshows a present non-uniform method of error sampling, which under cameraoperating perimeters similar to FIG. 12A only generated about 480 MB ofdata to be collected and processed. This is a reduction in storage andprocessing requirements by a factor of 30 over the prior art. FIG. 12Cillustrates a preferred non-uniform error sampling method using linearinterpolation. Under camera operating perimeters similar to FIG. 12A,this method only generated about 16 MB of data to be collected andprocessed. This is a reduction in storage and processing requirements bya factor of 30 over the prior art method of FIG. 12A.

As shown in FIGS. 6 and 12C, a selection can be made to utilize anoptimized subset image frames, which the present calibration does. Atthe beginning of the data collection cycle Ct, the changes in a pixelcell's circuit output signal over time 40 are more drastic. Because ofthis greater variability, the calibration data sets should include morerelatively reference frames from this portion of the collection cycle Ctthan towards the end of the collection cycle Ct where the output signalover time 40 can be relatively flatter. In a preferred embodiment, anautomatic method was used to allow the user to change exposure time(i.e. frame rate) and/or the off-time of the detector bias voltage 50,but the settings can be accomplished manually as well.

How to Select Which Pixels to Mask. Some of the pixels cells 29 in animaging device 28 are practically useless because of material andmanufacturing defects. Therefore, these pixels cells 29 have to beidentified and masked out, i.e., each of their outputs replaced withsome reasonable value calculated from the neighboring pixel cells 29.The present calibration method calculates a local average value of a setof neighboring pixel cell output signals and then compares this value toindividual pixel output signal values. This allows the calibrationmethod to adapt to a non-stationary radiation field. A preferredembodiment, calculated an average frame at least 5 complete datacollection cycles at a single reference radiation field intensitysetting. This provided a very robust and dependable determination inminimal time of the bad pixels cells 29 in an imaging device 28.

Calculating Replacement Values. After all the bad pixel cells 29 havebeen located, their values are replaced with their local arithmeticaverages. There for the output signal of a solitary bad pixel cell 29 isreplaced with the average of four good adjecent pixel output signals.The pixel output signal from the bad pixel cell 29 is excluded in thiscalculation. The four good adjacent pixel cells 29 were selected so thatall the possible directions were equally weighted. For example, if thepixel cell 29 above a first bad pixel cell 29 is also a bad, then eitherthe pixel cell 29 to up-left or up-right is used instead in calculatingthe replacement value for the pixel output signal of the first bad pixelcell 29.

Geometry Correction and Filling-in Inactive Zones. The relativepositions on the ASIC hybrids are ideally close and uniform, which meansthat there are some inactive areas (dead space) between adjacent hybridsand that the relative distances can vary between different adjacenthybrid. The solution to this problem is two-step. First, measurementswere made of the distances between hybrids and possible rotation anglesof hybrids based on a calibration image of a reference object. Then, theerrors were corrected based on these measurements. The measurements weremade by using the camera itself as a measuring device, and taking imageswith a calibrated reference object that has very accurate dimensions.Then after measuring the distances, the known and measured values werecompared and the mismatches detected.

Correction for Mismatches and Filling. After the exact positioning ofthe hybrids was known, a correction algorithm was implemented. Based onthe distances a grid was constructed which showed exactly where a givenpixel should lie in the image. Based on this, a bilinear interpolationmethod was used to get the sub-pixel translated and rotated new pixelvalues.

While the above description contains many specifics, these should not beconstrued as limitations on the scope of the invention, but rather asexemplifications of one or another preferred embodiment thereof. Manyother variations are possible, which would be obvious to one skilled inthe art. Accordingly, the scope of the invention should be determined bythe scope of the appended claims and their equivalents, and not just bythe embodiments.

1. A high energy, direct radiation conversion X-ray imaging systemcomprising: a high energy x-ray imaging camera, the camera having a highpixel density, direct conversion radiation detector substrate, withpixels of detector substrate, an electrical connection to acorresponding pixel circuit on an ASIC readout substrate, the detectorsubstrate providing for directly converting impinging high energy x-raygamma ray radiation to an electrical charge and communicating theelectrical charge via the electrical connection between the pixel to itscorresponding pixel circuit on the ASIC readout substrate as an electriccharge signal, and the pixel circuit providing for processing theelectric charge signal from each pixel; a high speed image frameprocessing module in electronic communication with the ASIC readoutsubstrate of the imaging camera, the frame processing module capable ofreceiving digitized pixel signals derived from an output from each pixelcircuit of the readout substrate and using the pixel signals to generatean image frame at a frame readout rate of greater than ten image framesper second; a calibration module selectably in digital communicationwith the frame processor module, the module when selected being drivenby a software process including a calibration routine which calibrationroutine writes pixel correction data specific to each pixel in an imageframe to a lookup table; a lookup table, the lookup table writeable bythe calibration module with pixel specific correction data, and readableby a normalization module; and a normalization module selectably incommunication with the frame processor module and with the lookup table,the normalization module receiving real time image frame data/recordfrom the frame processor module and pixel specific correction data fromthe lookup table, and providing normalized image data via a displayimage output for use in a display module to present an X-ray image ofthe high energy, direct detection X-ray imaging system.
 2. The highenergy, direct radiation conversion X-ray imaging system of claim 1,wherein the normalization module provides normalized image data via adisplay image output for use in a display module to present a dynamicX-ray image from the high energy, real time, direct detection X-rayimaging system.
 3. The high energy, direct radiation conversion X-rayimaging system of claim 1, wherein the normalization module providesnormalized image data via a display image output for use in a displaymodule to present a static X-ray image from the high energy, real time,direct detection X-ray imaging system.
 4. The high energy, directradiation conversion X-ray imaging system of claim 3, wherein thenormalization module accumulates normalized image data over a period oftime to provide a high precision display image output for use in adisplay module to present a static X-ray image.
 5. The high energy,direct radiation conversion X-ray imaging system of claim 2, wherein thenormalization module accumulates normalized image data over a period oftime of at least one hundredth of a second to ten seconds for providinga high precision display image output for each of the accumulationperiods, for use in a display module to present a dynamic X-ray image.6. The high energy, direct radiation conversion X-ray imaging system ofclaim 4, wherein the normalization module accumulates normalized imagedata over a period of time of at least one hundredth of a second to 300seconds.
 7. The high energy, direct radiation conversion X-ray imagingsystem of claim 4, wherein the normalization module accumulatesnormalized image data over a period of time of at least five minutes. 8.The high energy, direct radiation conversion X-ray imaging system ofclaim 1, wherein the camera module comprises an imaging device having aCadmium Telluride composition based radiation detector substrate incommunication with an ASIC readout substrate.
 9. The high energy, directradiation conversion X-ray imaging system of claim 8, wherein the cameramodule comprises an imaging device having a radiation detector substrateconsisting of a composition selected from the group consisting of:Cadmium-Telluride and Cadmium-Zinc-Telluride.
 10. The high energy,direct radiation conversion X-ray imaging system of claim 1, wherein thecamera module includes a detector substrate bias switch circuit.
 11. Thehigh energy, direct radiation conversion X-ray imaging system of claim1, wherein the high speed image frame processing module is capable ofreceiving digitized pixel signals derived from the output from eachpixel circuit of the readout substrate and using the digitized pixelsignals to generate an image frame at a frame readout rate of greaterthan 25 image frames per second.
 12. The high energy, direct radiationconversion X-ray imaging system of claim 1, wherein the high speed imageframe processing module is capable of receiving digitized pixel signalsderived from the output from each pixel circuit of the readout substrateand using the digitized pixel signals to generate an image frame at aframe readout rate of greater than 50 image frames per second.
 13. Thehigh energy, direct radiation conversion X-ray imaging system of claim1, wherein the software process includes a calibration routine whichanalyzes each digitized pixel value over at least some of the collectedcalibration frames being analyzed in accordance with a pixel valuecorrection algorithm to provide and write pixel value correction dataspecific to each pixel in an image frame to the lookup table
 14. Thehigh energy, direct radiation conversion X-ray imaging system of claim1, wherein the software driving the calibration module includes a pixelnon-linear performance compensation routine providing error correctionfor each pixel as a function of time.
 15. The software driving thecalibration module of claim 14, wherein the pixel non-linear performancecompensation routine includes an asymmetric linear polynomic calculationto determine correction coefficients to provide error correction foreach pixel as a function of time.